Generation Scotland: an update on Scotland's longitudinal family health study.

Purpose: Generation Scotland (GS) is a large family-based cohort study established as a longitudinal resource for research into the genetic, lifestyle and environmental determinants of physical and mental health. It comprises extensive genetic, sociodemographic and clinical data from volunteers in Scotland.

Participants: A total of 24 084 adult participants, including 5501 families, were recruited between 2006 and 2011.

Loneliness in the Digital World: protocol for a co-produced ecological momentary assessment study in adolescents.

Introduction: Loneliness has been identified as an important public health issue, peaking during adolescence. Previous research has suggested that social interaction is a key factor in loneliness, and positive social interaction can act as a protective factor against loneliness. However, it is unclear whether there are differing impacts of in-person and online social interaction on adolescents' loneliness and mental health.

Feasibility and ethics of using data from the Scottish newborn blood spot archive for research.

Background: Newborn heel prick blood spots are routinely used to screen for inborn errors of metabolism and life-limiting inherited disorders. The potential value of secondary data from newborn blood spot archives merits ethical consideration and assessment of feasibility for public benefit. Early life exposures and behaviours set health trajectories in childhood and later life.

TeenCovidLife: a resource to understand the impact of the COVID-19 pandemic on adolescents in Scotland.

TeenCovidLife is part of Generation Scotland's CovidLife projects, a set of longitudinal observational studies designed to assess the psychosocial and health impacts of the COVID-19 pandemic. TeenCovidLife focused on how adolescents in Scotland were coping during the pandemic. As of September 2021, Generation Scotland had conducted three TeenCovidLife surveys.

RuralCovidLife: A new resource for the impact of the pandemic on rural Scotland.

RuralCovidLife is part of Generation Scotland's CovidLife project, investigating the impact of the COVID-19 pandemic and mitigation measures on people in Scotland. The RuralCovidLife project focuses on Scotland's rural communities, and how they have been impacted by the pandemic. During survey development, Generation Scotland consulted with people living or working in rural communities, and collaborated with a patient and public involvement and engagement (PPIE) group composed of rural community leaders.

Blood-based epigenome-wide analyses of cognitive abilities.

Background: Blood-based markers of cognitive functioning might provide an accessible way to track neurodegeneration years prior to clinical manifestation of cognitive impairment and dementia.

Results: Using blood-based epigenome-wide analyses of general cognitive function, we show that individual differences in DNA methylation (DNAm) explain 35.0% of the variance in general cognitive function (g).

Epigenetic scores for the circulating proteome as tools for disease prediction.

Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNA methylation (DNAm) signatures of the circulating proteome and incident diseases.

CovidLife: a resource to understand mental health, well-being and behaviour during the COVID-19 pandemic in the UK.

CovidLife is a longitudinal observational study designed to investigate the impact of the COVID-19 pandemic on mental health, well-being and behaviour in adults living in the UK. In total, 18,518 participants (mean age = 56.43, SD = 14.

Mental health before and during the COVID-19 pandemic in two longitudinal UK population cohorts.

Background: The COVID-19 pandemic and mitigation measures are likely to have a marked effect on mental health. It is important to use longitudinal data to improve inferences.

Aims: To quantify the prevalence of depression, anxiety and mental well-being before and during the COVID-19 pandemic.

Accuracy of identifying incident stroke cases from linked health care data in UK Biobank.

Objective: In UK Biobank (UKB), a large population-based prospective study, cases of many diseases are ascertained through linkage to routinely collected, coded national health datasets. We assessed the accuracy of these for identifying incident strokes.

Methods: In a regional UKB subpopulation (n = 17,249), we identified all participants with ≥1 code signifying a first stroke after recruitment (incident stroke-coded cases) in linked hospital admission, primary care, or death record data.

Identifying dementia outcomes in UK Biobank: a validation study of primary care, hospital admissions and mortality data.

Prospective, population-based studies that recruit participants in mid-life are valuable resources for dementia research. Follow-up in these studies is often through linkage to routinely-collected healthcare datasets. We investigated the accuracy of these datasets for dementia case ascertainment in a validation study using data from UK Biobank-an open access, population-based study of > 500,000 adults aged 40-69 years at recruitment in 2006-2010.

Algorithms for the Capture and Adjudication of Prevalent and Incident Diabetes in UK Biobank.

Objectives: UK Biobank is a UK-wide cohort of 502,655 people aged 40-69, recruited from National Health Service registrants between 2006-10, with healthcare data linkage. Type 2 diabetes is a key exposure and outcome. We developed algorithms to define prevalent and incident diabetes for UK Biobank.